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Abstract

Background

To preserve muscle mass and therefore limit the risk of disability in older adults
protein intake is seen as important factor. Besides the amount of protein, its distribution
over the day is thought to affect protein anabolism. This cross-sectional study investigates
the association between the amount and distribution of protein intake and frailty
in older adults.

Methods

In 194 community-dwelling seniors (≥75 years) amount of protein intake and its distribution
over the day (morning, noon, evening) were assessed using a food frequency questionnaire.
Unevenness of protein distribution was calculated as coefficient of variation (CV).
Frailty was defined as the presence of at least three, pre-frailty as the presence
of one or two of the following criteria: weight loss, exhaustion, low physical activity,
low handgrip strength and slow walking speed.

Conclusions

In this sample of healthy older persons, amount of protein intake was not associated
with frailty, but distribution of protein intake was significantly different between
frail, pre-frail and non-frail participants. More clinical studies are needed to further
clarify the relation between protein intake and frailty.

Keywords:

Background

Frailty is a highly relevant geriatric syndrome which is mainly characterized by a
loss of physical performance, owing to the age associated decrease of muscle mass
and muscle function (sarcopenia) [1]. To preserve muscle mass and therefore limit the risk of disability in older adults,
an adequate protein intake is seen as one important factor [2].

The amount of dietary protein directly affects nitrogen-balance and protein turnover.
Essential amino acids are especially crucial for muscle protein synthesis. In a large
cohort study in older men and women (Health, Aging and Body Composition study) over
three years, lean mass decreased 40% less in the highest quintile of protein intake
than in the lowest [3]. Comparing an intervention with a protein intake of 0.45 g/kg BW vs. 0.92 g/kg BW
Castaneda et al. [4] found a decrease of lean tissue, muscle function and immune response in the “low
protein” group after 9 weeks, whereas lean mass, muscle and immune function were preserved
at the higher intake level.

Recently, an association between protein intake and physical performance has been
identified in the Hertfordshire Cohort study. In this cross-sectional analysis association
between higher percentage of energy from protein and faster 3 m walk was found in
community-dwelling women [5]. In the InCHIANTI study, a cross-sectional study in more than 800 older Italians,
the risk of being frail was twice as high in the lowest quintile of protein intake
compared to higher intakes [6]. These results were confirmed by Beasley et al. [7] who described a lower risk of frailty after three years in older women with high
protein intakes at baseline (Women’s Health Initiative Observational Study).

There is evidence that nitrogen turnover is not only influenced by the amount, but
also by the pattern of protein feeding. El-Khoury et al. [8] found lower nitrogen excretion with a feeding pattern of three main meals compared
to multiple small meals in an intervention study in healthy young adults. In older
adults, Arnal et al. [9] described that a pulse protein feeding pattern (~80% of daily protein for flunch)
is more efficient in improving nitrogen retention than a spread feeding pattern (four
smaller meals with similar amounts of protein). The association between the distribution
of protein intake over the day and physical performance or frailty has not been investigated
before.

The aim of this study was to investigate the association between the amount and distribution
of dietary protein and frailty in older adults.

Methods

For this cross-sectional study 206 volunteers living independently at home were recruited
from August 2009 to September 2010 in the region of Nürnberg (Germany). Potential
participants were sought through a newspaper advertisement and via personal contact
in a day clinic and a rehabilitation center. In order to be included, participants
needed to be 75 years or older, not suffering from any illness that profoundly impacted
their diet and should not show signs of significant cognitive impairment (Mini Mental
State Examination ≥ 24 out of 30 points [10]). The assessments took place either at the study site or participants were visited
at home, if they were not able or willing to attend the study clinic. This study was
conducted according to the guidelines laid down in the Declaration of Helsinki and
all procedures were approved by the ethics committee of the Friedrich-Alexander-Universität
Erlangen-Nürnberg. Written informed consent was obtained from all subjects.

Sample characteristics

The living situation was assessed as self-reported “living alone” or “not living alone”.
The educational level of participants with only elementary school or no degree was
defined as “low”, “medium” for those who attended a secondary school and “high” for
participants with a university entrance diploma or higher degrees.

Participants’ height and weight were measured standing upright without shoes in light
clothing. BMI was calculated for each subject as weight [kg]/height2 [m2].

The questionnaire on instrumental activities of daily living (IADL, 8 questions, max.
8 points) of Lawton and Browdy [11] was used to assess the degree of dependency in everyday life. A lower score designates
a higher level of dependency. The participants’ answers on the IADL items dealing
with dependency in going shopping and cooking meals were separately evaluated and
documented as “goes shopping independently” and “cooks independently” vs. “needs help
with shopping” and “needs help with cooking”. The use of medication was recorded as
“more than three medications” or “less than three medications”. The Charlson Comorbidity
Index (CCI) was used to assess comorbid conditions. From 19 diseases, weighted with
1, 2, 3 or 6 points, that have been found to increase mortality, a sum-score is calculated,
with a higher score pointing to a higher mortality risk [12]. Reported chewing and swallowing difficulties were also documented.

Assessment of frailty

We used the frailty definition of Fried et al. [13] and therefore assessed the following five criteria: weight loss (self-reported, more
than 4.5 kg in the last year), exhaustion (self-reported feeling that everything was
an effort or that one could not “get going” more than 2 times a week), low grip strength
(Jamar dynamometer, men ≤ 29–32 kg, women ≤ 17–21 kg stratified by BMI quartiles of
the original study sample of Fried et al. [13]), low walking speed (depending on gender and height > 6–7 sec/ 4.57 m,) and low physical
activity (men < 1.6 kJ (383 kcal)/ week, women < 1.1 kJ (270 kcal)/ week) estimated
with the short form of the Minnesota Leisure Time Activities Questionnaire [14]. The cut off values for grip strength, walking speed and physical activity were derived
from the lowest sex specific quintiles of the original study population of Fried et
al. [13]. Subjects without any of these five attributes were categorized as non-frail, those
with one or two positive criteria as pre-frail and those with three or more as frail.

Nutritional assessment

In a personal interview usual food intake was estimated using a slightly modified
form of the food frequency questionnaire (FFQ) of the German part of the European Prospective Investigation into Cancer and Nutrition[15], which consists of 103 food items. Within this tool questions on the usual consumption
of foods and food groups during the last 12 months are asked based on standard portion
sizes (e. g. 1 cup, 1 piece, 1 teaspoon per month/ week/ day). Additionally there
are questions on the kinds of fats used and the use of dietary supplements. The modifications
mentioned above affected the definition of 12 food items to comply within our research
objectives (e.g. subdividing the category “fish” into three categories of fish with
different contents of fat and protein). Furthermore, the categories “bacon” and “salty
snacks” were added, as they may contribute considerably to energy intake. Also a question
on the consumption of unrefined cereals was added.

46 items of the FFQ were identified as main protein sources i. e. all foods derived
from animal products (meat, egg, milk, fish), cereals (e. g. bread, rice, pasta) and
protein rich vegetables (potatoes, legumes, soy). For these main protein sources the
usual time(s) of consumption (morning, noon, evening) was asked in addition to the
frequency of consumption.

From standard portions and frequencies of consumption, all items were converted to
g/d. Daily energy and protein intake were calculated using the German nutrient database
“Bundeslebensmittelschlüssel” (BLS II.3 [16]). Average daily protein intake is expressed as grams per day (g/d), grams per kg
body weight (g/kg BW) and as percentage of daily energy intake (E%). Energy intake
is expressed as kJ/d and kJ/kg BW. The amount of protein ingested per meal was ascertained
by summing up the amounts of protein of the main protein sources for each meal. If
more than one mealtime was indicated, an equal distribution of the portions over the
indicated mealtimes was postulated.

Data analysis and statistics

For all statistical analyses SPSS 20.0 (IBM) software was used.

Sample characteristics are presented as median (min-max.) for continuous variables
and as percent for categorial variables. The distribution of the prevalence of participants’
characteristics in the three frailty groups was tested for significant differences
by χ2 testing.

Differences in continuous sample characteristics, daily protein intake (g, g/kg BW,
E%) as well as in distribution of protein intake (%) over the three mealtimes in non-
frail, pre-frail and frail participants were tested for significance by Kruskall-Wallis
test. A coefficient of variation (CV = SD/ mean value) of protein intake (g/meal)
in the morning, at noon and in the evening was calculated for every participant to
estimate the unevenness of the distribution of protein intake over the day. The CV
is a dimensionless, relative measure of statistical dispersion. A CV of zero connotes
a total evenness of the protein intake over the day, i. e. the same amount of protein
is ingested in the morning, at noon and in the evening. The more uneven the distribution
is, the higher is the individual CV of protein intake. CV is presented as median (min.-max.)
for each of the three frailty groups and compared by Kruskal-Wallis testing. Distribution
of the CV of protein intake in the single, dichotomous frailty criteria was compared
by Mann-Whitney-U testing.

The risk of being frail or pre-frail vs. non frail and the risk of each single frailty
criterion, respectively, in the 2nd, 3rd and 4th quartile of protein intake (g/kg
BW) vs. the 1st quartile (lowest intake) was calculated as odds ratios (OR) accompanied
by 95% confidence intervals by multinomial logistic regression analyses. Confounding
covariates were identified by ‘manual backward elimination’ with exclusion if an initially
included factor was both insignificant and did not cause a change-in-estimate of > 10%
of the exposure of interest.

Results

194 study subjects (68 men and 127 women) providing complete information (less than
three items missing) on the FFQ were included in the following analysis. Participants
had a median age of 83 (75–96) years. Pre-frailty was found in 40.5% of the participants
and 15.4% were frail.

The three frailty groups differed significantly in the distribution of sex (P < 0.05)
and age (P < 0.001) (Table 1). Frail participants lived alone more often than pre-frail and non-frail (P < 0.05)
and had a lower educational level. Median BMI was 27.1 (18.6-36.1) kg/m2 without significant differences between the three groups. Frail participants scored
significantly higher on the CCI and were more likely to use more than three medications
than pre-frail and non-frail persons (P < 0.05). Chewing and swallowing difficulties
were significantly more prevalent with increasing frailty status. Median daily energy
intake was 8.5 (4.4–14.9) kJ without differences between the three frailty groups
(Table 1).

Median (min.-max.) daily protein intake was 77.5 (38.5–131.5) g, 1.07 (0.58–2.27)
g/kg BW and 15.9 (11.2–21.8) E%. A trend in the amount of protein ingested could not
be identified with increasing frailty status (Table 2). Accordingly, we found no differences in the risk of frailty or its single criteria
in quartiles of higher protein intake compared to the quartile with the lowest intake.
We only found a significant p for trend concerning low physical activity (Table 3).

Table 2.Amounta of daily protein intake in three frailty groups as g/day, g/kg BW and E%

Table 3.Riska of frailty, pre-frailty and of the single frailty criteria in the quartiles of protein
intake [g/kg BW]b

The main protein sources covered a median (min.-max.) of 73.8 (45.7–90.5) % of total
protein intake. Most of this protein was ingested at noon (60.2 (0.0–84.5)%), about
one fourth (25.1 (0.2–70.5)%) in the evening and 15.3 (0.0–47.4) % in the morning.
With increasing frailty, the percentage of protein ingested in the morning decreased
significantly, whereas it increased at noon (Table 4).

Table 4.Percentage of protein ingested in the morning, at noon and in the evening in three
frailty groups [median (min.-max.)]

Figure 1.Boxplots of coefficient of variation (CV) of protein distribution over the three daily
mealtimes in non-frail, pre-frail and frail participants. The boxes represent the interquartile range with the bold horizontal lines denoting
median CV. The whiskers show the highest and lowest values within 1.5 box lengths
from either end of the box and the circles represent outliers. Kruskall-Wallis testing
showed that the median CV differed significantly between the three frailty groups
(P < 0.05).

Table 5.Coefficient of variation (CV) of protein distribution over the three daily mealtimes
[median (min.-max.)] in participants with and without the single frailty criteria

Discussion

In this study no differences were found in the amount of protein intake between frail,
pre-frail and non-frail community-dwelling older adults. With regard to the distribution
of protein intake, frail subjects showed a different and more uneven distribution
of their protein intake over the day with lower intake at breakfast and higher intake
at lunch. To our knowledge this is the first study investigating the association between
the distribution of protein intake and frailty.

Contrary to Bartali et al. [6], who found an association between low protein intake (lowest quintile) and frailty
in a cross-sectional analysis of the InCHIANTI study, in our sample the risk of frailty
was not reduced in the quartiles of higher intakes compared to the quartile of the
lowest protein intake. Furthermore, there is some evidence on the association of protein
intake with walking speed [5] as well as handgrip strength [17], which we could also not identify in our analyses. This might be due to the relatively
high protein intake even in the lowest quartile, where the cut off was ≥0.9 g/kg BW
protein/day. This is above the value of 0.8 g/kg which is the present recommendation
for protein intake in younger as well as in older adults [18], and has been found to be a threshold for negative nitrogen balance [19], low muscle mass [20] and more health problems after 10 years [21].

Our study is the first to investigate the association between the distribution of
protein over all the meals and frailty. Regarding evenness of this distribution we
found a more even protein eating pattern in non-frail participants than in frail and
pre-frail (Figure 1) and in those reporting exhaustion and slow walking speed (Table 5). These results are in line with the recommendations of Paddon-Jones et al. [22] to equally distribute the daily protein intake of older adults over breakfast, lunch
and dinner. Arnal et al. [9], in contrast, found one large serving of protein (80% of daily protein intake in
one of three meals) to be more effective to promote a positive nitrogen balance and
muscle synthesis in older adults than protein intake evenly spread over four meals.
This discrepancy may be explained by the low absolute amount of daily protein administered
to Arnal et al.’s participants (approx. 65 g). That means that in the spread feeding
group a single meal contained hardly 20 g of protein, the minimum needed for stimulating
muscle protein synthesis according to Paddon-Jones et al. [22], whereas with a higher total daily protein intake, as found in our sample, an even
distribution results in more meals containing at least 20 g protein. At the same time,
fasting losses between meals, which increase with the amount of protein of the meal
[23], are reduced in a more even distribution. Finally, comparing our data with trials
on nitrogen balance and muscle protein synthesis we must be aware of the fact that
these results may not be totally transferable to issues of physical performance and
frailty.

For the assessment of usual dietary habits, we used the FFQ of the German part of
the EPIC study, which is well validated [24]. A limitation of this questionnaire is the proven underreporting of energy and protein
intake of about 20% [24]. Thus, actual protein intake in our participants is supposedly higher. The validity
of the results on distribution of protein intake are limited by the fact that although
our 46 a priori set of main protein sources obviously covered all important sources of actual dietary
protein, they still left an average of 26.2% of dietary protein undocumented. This
may be due to some of our participants consuming very small amounts of protein, mainly
from vegetable foods that were not considered as main protein sources, e. g. fruit
(especially bananas) and vegetables (especially tomato sauce).

We are aware of the limitation that we only assessed protein intake at the main meals
and only for selected foods. This was decided to avoid an undue length of the FFQ,
which would probably have overstressed our aged participants. On the other hand Roussett
et al. [25] found in a cross-sectional study in healthy older adults, that snacks only contributed
to 1.4% in men and 2.3% in women to protein intake. Therefore snacks were seen as
negligible in our distribution analysis. Up to now, there is no common method for
evaluating protein distribution over all meals. Using the CV as measure for unevenness
of distribution can be seen as a first approach. Certainly, assessment tools have
to be developed to enable a more detailed evaluation of meal habits and statistical
methods have to be adapted to further clarify the impact of protein distribution on
sarcopenia, physical performance and frailty.

A major limitation of the study is its cross-sectional design which does not allow
any statements on causal relationship. It is also plausible that frailty vice versa
affects protein intake, for example by impairments in going shopping, chewing or swallowing
(Table 1). Another critical point is that we did not consider the influence of protein quality
on frailty, although it is an important regulator of protein metabolism. The small
sample size, especially in the group of frail participants limits the study’s statistical
power. Nevertheless, we detected significant associations. Furthermore, the sample
consists of volunteers and may therefore lack in representation of the older German
population in general.

A strong advantage of our study is that all FFQ have been conducted in personal interviews
by a single experienced nutritionist, and for all assessments well validated tools
have been used. This is the first study investigating the distribution of protein
intake in German older adults and the association between this distribution and frailty.
Unique is the development of a parameter of unevenness of protein distribution, which
to our knowledge has not been used before in this setting.

In summary, in our study group of very old independently living senior citizens only
few were frail and even the lowest quartile of protein intake was above the recommendation
of 0.8 g/kg BW. There was no significant difference in the amount of protein ingested
between frailty groups and we found no reduced risk for frailty in the quartiles with
a higher protein intake compared to the lowest quartile. Our results also showed a
relation between frailty and the distribution of daily protein intake over the main
meals. Studies on the effect of protein intake on functional and clinical outcomes
are still scarce. Therefore we recommend further investigation on this topic on the
basis of the results of our study.

Competing interest

The authors declare that they have no competing interests.

Authors’ contributions

The authors’ responsibilities were as follows: DV, JMB and CCS designed the research.
JB, MJK and RD conducted the research. JB analyzed the data and performed statistical
analyses. WU supervised the statistical analysis. JB drafted the manuscript with appreciable
input from DV. JB and DV had prime responsibility for the final manuscript content.
JMB, MJK, CCS, WU also contributed to the final manuscript. All authors read and approved
the final manuscript.

Acknowledgements

We thank Klaus Issel and Dr. Cramer-Ebner for their help in approaching older individuals,
Lisa Schmölz and Sabine Ehrhardt for their assistance in entering data. We especially
thank all of the volunteers for their valuable cooperation.

This work was partly supported by Nestlé HealthCare Nutrition, Lausanne, Switzerland
and the Theo und Friedl Schöller-Stiftung, Nürnberg, Germany.

Subcommittee on the Tenth Edition of the Recommended Dietary Allowances, Food and
Nutrition Board, Commission on Life Sciences, National Research Council: Recommended Dietary Allowances. 10th edition. Washington, D.C: The National Academies Press; 1989.